7results about How to "Increase loyalty" patented technology

The invention provides a live broadcast goods carrying scene optimization method and system combined with digital multimedia, and relates to the technical field of digital multimedia, and the method comprises the steps: firstly obtaining the cognitive association data of a live broadcast goods carrying scene, including the commodity cognitive multimedia content, the user cognitive behavior record and the commodity information set; then, based on the cognitive association data, establishing a corresponding relationship between the user cognitive behavior record and the commodity cognitive multimedia content, and generating a cognitive rhythm adaptation sequence; user cognitive behavior records and cognitive stage entries are matched in real time in live broadcast, and the commodity cognitive multimedia content is adjusted according to the adjustment rule parameter set; and collecting user subsequent behavior data during the adaptation period, adjusting the cognitive rhythm adaptation sequence after correlation analysis, generating a digital multimedia cognitive adaptation strategy, and applying the digital multimedia cognitive adaptation strategy to subsequent live broadcast. The live broadcast goods carrying effect and the user experience can be improved.

Embodiments of the present application provide a home configuration method, device, equipment and medium, the method comprises: obtaining the home configuration demand information of a target user; determining the data score level of the target user according to the home configuration demand information of the target user and preset data score rules; obtaining the target recommendation model according to the data score level of the target user; determining the target home configuration information according to the home configuration demand information of the target user and the target recommendation model; the configuration scheme meeting the user demand can be automatically and quickly generated, the configuration efficiency is significantly improved, the user waiting time is shortened, the user demand is accurately met, and the user experience and satisfaction are improved.

This application discloses an odor-proof main structure and a cat litter box, relating to the field of pet product technology. The odor-proof main structure includes a litter bin and a base. The litter bin is rotatably mounted on the top of the base. The top of the base has a recessed cavity into which the bottom of the litter bin extends. A uniform rotational gap is formed between the inner wall of the recessed cavity and the litter bin. A collection port is located at the bottom of the recessed cavity. A sealing ring is installed at the bottom of the litter bin. The sealing ring is in sealed contact with the inner wall of the recessed cavity. When the litter bin is in its initial position, the projection outline of the sealing ring on the ground is outside the projection outline of the collection port on the ground. This odor-proof main structure effectively prevents odors from escaping from the litter bin, effectively reduces noise, and maintains a simple structure, facilitating disassembly and cleaning.

The invention discloses a human resource data visual management method and system based on a semantic analysis technology, and relates to the technical field of human resource management.The method comprises the steps that digital production data and text production data of employees are collected and analyzed, and employee evaluation indexes are determined; performing normalization processing on the digital production data and the text production data, calculating expected output, and determining an employee ability evaluation level; constructing a neural network evaluation model, and training the neural network evaluation model by using the digital production data and the text production data until the model converges; and evaluating the employee ability by using the converged neural network evaluation model, and outputting an employee evaluation level. According to the method, the digital production data and the text production data of the employees are collected at the same time, preprocessing and semantic analysis are carried out, dominant and implicit information in the human resource data can be more comprehensively mined, and the problem that key information is difficult to rapidly and accurately extract in a traditional data processing mode is solved.

This invention relates to a knowledge graph-based intelligent customer service question-and-answer precision recommendation and processing method, belonging to the field of electronic digital data technology. The method includes: constructing a conversation prediction knowledge graph based on the historical conversation counts from multiple channels; predicting the future conversation counts from multiple channels based on the conversation prediction knowledge graph and the current conversation counts from multiple channels; setting the number of robot agents and human agents based on the future conversation counts from multiple channels; accessing conversations from multiple channels, using robot agents to perform semantic understanding of user questions in the conversation, constructing a user demand profile, and determining whether to assign a human agent; if so, assigning the optimal human agent based on the status data of the human agent; if not, generating answers based on the user demand profile, conducting a dialogue, and generating recommended questions based on a question association graph. The question association graph records the relationships between multiple questions, which has the advantage of improving the quality and efficiency of customer service.

The invention relates to the technical field of electronic commerce, artificial intelligence and information retrieval, and discloses a point shopping mall multi-modal search method based on a vectorization search architecture. According to the core scheme, the method comprises the following steps: receiving multi-mode search input of user texts, images, audios, videos and the like, realizing efficient transmission and fusion processing through RTC and ITC technologies, and generating unified semantic representation; in combination with LLM and ELCTRA algorithms, deep semantic understanding is carried out, and a user query intention vector is generated; the method comprises the following steps: constructing a commodity multi-modal feature vector library (encoding through an ELCTRA / ResNet-50 / WaveNet embedded model group) and a user portrait vector library, and constructing a dynamically updated vector index based on an HNSW algorithm; a candidate commodity set is retrieved by using an ANN algorithm, and personalized sorting is realized through an L2R sorting model (fusing multi-dimensional factors such as user portrait matching degree and commodity correlation); collecting user behavior data, and regularly finely adjusting model parameters and updating indexes through incremental learning. According to the method, the bottleneck of traditional keyword search is broken through, millisecond-level high-concurrency retrieval is realized, the search accuracy and personalized experience are improved, meanwhile, data support is provided for shopping mall operation, the problem of data drift is effectively relieved, and the method is suitable for high-concurrency and multi-mode search scenes of integral shopping malls.

The application relates to the technical field of tobacco flavor, and discloses a method for improving the sensory quality of caramelly sweet tobacco leaves, which uses tobacco leaves with relatively poor quality in the caramelly sweet tobacco leaf producing area as raw materials, develops tobacco extracts through biotechnology and multi-stage separation technology, and respectively prepares functional intensive flavor L and style intensive flavor X through flavor adjusting means, so that the aroma and taste of the caramelly sweet tobacco leaves can be enhanced, the attractiveness and comfort degree can be improved, and through grading separation and accurate proportioning, the proportion of different components in the tobacco extracts can be more suitable, so that the taste of the tobacco can be improved, the tobacco is more rich and balanced, the preparation method and the accurate proportioning can produce unique tobacco taste and aroma, the product can help to establish a differentiated competitive advantage in the market, in addition, through improving the sensory quality and taste of the tobacco leaves, the satisfaction of smokers can be improved, and the recognition and loyalty of the product can be improved.